Point-in-time backups via a storage controller to an object storage cloud

ABSTRACT

A storage controller receives a command from a host application to perform a point-in-time backup of a source dataset to a storage cloud. The storage controller generates a target dataset via a point-in-time copy of the source dataset, and a mapping that indicates a correspondence between locations of the source dataset and locations of the target dataset. The storage controller copies the target dataset to the storage cloud to generate a backup dataset that is the point-in-time backup of the source dataset, wherein the backup dataset is accessible via reference to the locations of the source dataset.

BACKGROUND 1. Field

Embodiments relate to point-in-time backups via a storage controller toan object storage cloud.

2. Background

Cloud storage is a model of data storage in which digital data is storedin logical pools, and the physical storage spans a plurality of servers.The physical storage environment may be owned and managed by a hostingcompany. These cloud storage providers may be responsible for keepingthe data available and accessible, and for keeping the physicalenvironment protected and maintained properly. People and organizationsmay buy or lease storage capacity from the cloud storage providers tostore user, organization, or application data.

In certain computing environments, a storage controller allows hostcomputing systems to perform input/output (I/O) operations with aplurality of storage devices controlled by the storage controller. Astorage management application that executes in the storage controllermay manage the plurality of storage devices, such as disk drives, tapedrives, flash drives, direct access storage devices (DASD), etc., thatare coupled to the storage controller. A host application that executesin a host computing system may transmit I/O commands to the storagecontroller and the storage controller may execute the I/O commands toread data from the storage devices or write data to the storage devices.

A point-in-time copy is a fully usable copy of a defined collection ofdata that includes an image of the data as it appeared at a singlepoint-in-time. The point-in-time copy is considered to have logicallyoccurred at the single point-in-time, but certain mechanisms may performpart or all of the copy at other times, as long as the result is aconsistent copy of the data as it appeared at the single point-in-time,Prior to the use of point-in-time copy operations, in order to create aconsistent copy of the data, a host application had to be stopped whilethe data was being physically copied. For large datasets, this causedstoppages of several hours, and made the process of making copies oflarge datasets very inconvenient for users. Point-in-time copyoperations allow a copy to be created with almost no impact on the hostapplication. Except for a brief period of a few milliseconds or secondswhile the point-in-time copy is established, the host application cancontinue running. For example FlashCopy* supported by InternationalBusiness Machines (IBM) is a point-in-time copy mechanism that makes itpossible to create, nearly instantaneously, point-in-time snapshotcopies of entire logical volumes or data sets. * IBM, zSeries, pSeries,xSeries, BladeCenter, WebSphere, and DB2, FlashCopy are trademarks ofInternational Business Machines Corporation registered in manyjurisdictions worldwide.

SUMMARY OF THE PREFERRED EMBODIMENTS

Provided are a method, system, and computer program product in which astorage controller receives a command from a host application to performa point-in-time backup of a source dataset to a storage cloud. Thestorage controller generates a target dataset via a point-in-time copyof the source dataset, and a mapping that indicates a correspondencebetween locations of the source dataset and locations of the targetdataset. The storage controller copies the target dataset to the storagecloud to generate a backup dataset that is the point-in-time backup ofthe source dataset, where the backup dataset is accessible via referenceto the locations of the source dataset. As a result, the storagecontroller rather than a host performs the point-in-time backup of thesource dataset to the storage cloud.

In further embodiments, the host application executes in a hostcomputational device that is coupled to the storage controller, whereoperations for performing the point-in-time backup of the source datasetto the storage cloud is offloaded to the storage controller from thehost computational device. The storage controller copies the targetdataset to the storage cloud without transmitting extents, tracks, orother storage entities of the target dataset to the host computationaldevice. As a result, operations for generating the point-in-time backupare offloaded to the storage controller.

In certain embodiments, the point-in-time backup of the source datasetto the storage cloud is performed by a virtual concurrent copy session,where in response to termination of the virtual concurrent copy session,resources allocated for the mapping that indicates the correspondencebetween locations of the source dataset and locations of the targetdataset are freed. As a result, resources that are not needed by thestorage controller are freed.

In additional embodiments, the storage controller receives aninput/output (I/O) request from a host computational device. In responseto determining that a track corresponding to the I/O request has beenupdated in the target dataset, the storage controller sends the I/Orequest to target dataset extents for the track. As a result, the I/Orequest is satisfied by the target dataset.

In yet additional embodiments, the storage controller receives aninput/output (I/O) request from a host computational device. In responseto determining that a track corresponding to the I/O request has notbeen updated in the target dataset, the storage controller sends the I/Orequest to source dataset extents for the track. As a result, the I/Orequest is satisfied by the source dataset.

In certain embodiments, the mapping that indicates a correspondencebetween the locations of the source dataset and the locations of thetarget dataset maps individual extents, or extent ranges, or volumes andassociated cylinder ranges via one to one, many to one, and one to manycorrespondences. As a result, the mapping may be used for differenttypes of representation of storage.

Provided also is a cloud computing system, comprising a storage cloud, astorage controller coupled to the storage cloud, and a host coupled tothe storage controller. In the cloud computing system a storagecontroller receives a command from a host application to perform apoint-in-time backup of a source dataset to a storage cloud. The storagecontroller generates a target dataset via a point-in-time copy of thesource dataset, and a mapping that indicates a correspondence betweenlocations of the source dataset and locations of the target dataset. Thestorage controller copies the target dataset to the storage cloud togenerate a backup dataset that is the point-in-time backup of the sourcedataset, where the backup dataset is accessible via reference to thelocations of the source dataset. As a result, the virtual concurrentcopy is performed in a cloud computing system.

Provided also is a host computational device, comprising a memory, and aprocessor coupled to the memory, where the processor transmits a commandfrom a host application to a storage controller to perform apoint-in-time backup of a source dataset to a storage cloud, and wherethe storage controller generates a target dataset via a point-in-timecopy of the source dataset, and a mapping that indicates acorrespondence between locations of the source dataset and locations ofthe target dataset, and copies the target dataset to the storage cloudto generate a backup dataset that is the point-in-time backup of thesource dataset. The host application accesses the backup dataset viareference to the locations of the source dataset. As a result, the hostcomputational device offloads the performing of virtual concurrent copyto a storage controller.

BRIEF DESCRIPTION OF THE DRAWINGS

Referring now to the drawings in which like reference numbers representcorresponding parts throughout:

FIG. 1 illustrates a block diagram of a computing environment comprisinga storage controller coupled to one or more hosts and a storage cloud,in accordance with certain embodiments;

FIG. 2 illustrates a block diagram that shows the generation of apoint-in-time backup dataset via mapping of individual extents, inaccordance with certain embodiments;

FIG. 3 illustrates a block diagram that shows the generation of apoint-in-time backup dataset via mapping of extent ranges, in accordancewith certain embodiments;

FIG. 4 illustrates a block diagram that shows the generation of apoint-in-time backup dataset via mapping of volumes and cylinders, inaccordance with certain embodiments;

FIG. 5 illustrates a first flowchart that shows generation of apoint-in-time backup dataset, in accordance with certain embodiments;

FIG. 6 illustrates a second flowchart that shows generation of apoint-in-time backup dataset, in accordance with certain embodiments;

FIG. 7 illustrates a third flowchart that shows generation of apoint-in-time backup dataset, in accordance with certain embodiments;

FIG. 8 illustrates a block diagram of a cloud computing environment, inaccordance with certain embodiments;

FIG. 9 illustrates a block diagram of further details of the cloudcomputing environment of FIG. 8, in accordance with certain embodiments;and

FIG. 10 illustrates a block diagram of a computational system that showscertain elements that may be included in the storage controllers, thehost(s), and/or the storage cloud as described in FIGS. 1-9, inaccordance with certain embodiments.

DETAILED DESCRIPTION

In the following description, reference is made to the accompanyingdrawings which thrill a part hereof and which illustrate severalembodiments. It is understood that other embodiments may be utilized andstructural and operational changes may be made.

Backup and archiving solutions may include an object storage cloud as anoffline tier. Certain solutions target inactive data that may be movedfrom the online storage tier to the offline storage tier. This isreferred to as archiving, and the data is moved to the offline cloudtier and deleted from primary direct access storage devices (DASD).Since data is inactive there are no users or applications that haveaccessed the data for some period of time, so locking the dataset forthe time it takes to perform the archiving does not disrupt operations.

A backup is different from an archive in that after a dataset is movedto an offline cloud tier the dataset is also maintained in the onlineDASD tier for users and applications to access the dataset. For backup,the dataset should only be locked and inaccessible to users andapplications for as short a period of time as possible. Certainembodiments provide mechanisms to back up datasets to an object storagecloud with minimal interruption to users and applications that accessthe dataset.

Concurrent copy refers to a mechanism that allows a user to generate acopy of the data while applications are updating that data. Virtualconcurrent copy mechanisms extend the concurrent copy mechanisms, and invirtual concurrent copy mechanisms a point-in-time copy of the data ismade from a source location to an intermediate location, and the data isgradually copied from the intermediate location to target location viastandard I/O methods. The virtual concurrent copy operation is logicallycomplete after the source data is instantaneously copied (i.e., copiedvia point-in-time copy mechanisms) to the intermediate location, and isphysically complete after the data is moved to the target media of thetarget location. Certain embodiments provide mechanisms for apoint-in-time backup to an object storage cloud using a modified virtualconcurrent copy mechanism, A backup to an offline cloud tier isperformed as a MO pass process, The first pass gathers the extents ofthe source dataset and establishes a point-in-time copy session of thetracks of these extents. The second pass issues a command to the storagecontroller to offload the tracks from the target of the point in timecopy to the offline cloud tier. In certain embodiments, the modifiedvirtual concurrent copy operations for generating point-in-time backupto a storage cloud are performed by a storage controller. The hostoffloads the responsibility of generating the point-in-time backup tothe storage controller.

Exemplary Embodiments

FIG. 1 illustrates a block diagram of a computing environment 100comprising a storage controller 102 coupled to one or more hosts 104 anda storage cloud 106, in accordance with certain embodiments.

The storage controller 102 and the host 104 may comprise any suitablecomputational device including those presently known in the art, suchas, a personal computer, a workstation, a server, a mainframe, a handheld computer, a palm top computer, a telephony device, a networkappliance, a blade computer, a processing device, a controller, etc. Thestorage cloud 106 may he comprised of a plurality of storage devices(not shown), such as storage disks, tape drives, solid state disks,etc., and a computational device (not shown) that controls access to theplurality of storage devices of the storage cloud 106.

The storage controller 102, the host 104, and the storage cloud 106 maybe elements in any suitable network, such as, a storage area network, awide area network, the Internet, an intranet, etc. In certainembodiments, the storage controller 102, the host 104, and the storagecloud 106 may be elements in a cloud computing environment.

A storage management application 108 that executes in the storagecontroller 102 receives I/O commands from one or more host applications110 that execute in the host 104 and responds to the I/O commands byreading or writing data with respect to storage volumes stored thestorage cloud 106 or in storage devices 112, 114 coupled to the storagecontroller 102, where the storage devices 112, 114 may be comprised ofhard disks, solid state disks, or other storage devices. In certainembodiments, the storage management application 108 and the hostapplication 110 may be implemented in software, hardware, firmware orany combination thereof.

In certain embodiments, the host application 110 that executes in thehost 104 sends a request to the storage controller 102 to perform apoint-in-time backup of a source dataset 116 whose logical storagevolumes are controlled by the storage controller 102 and accessed by thehost application 110 via the storage controller 102. The source dataset116 may comprise a collection of data records stored in extents, tracks,blocks, or any other type of units in which storage may be represented.In certain embodiments, the storage management application 108 of thestorage controller 102 generates a point-in-time copy of the sourcedataset 116 via point-in-time copy operations 118, where thepoint-in-time copy is stored in a target dataset 120. The storagemanagement application 108 copies tracks (or other units, such asblocks, extents, etc.) of the target dataset 120 to the storage cloud106 to generate a backup dataset 124 in the storage cloud, concurrentlywith the point-in-time copy operations 118. The objects 126 of thebackup dataset 124 may be named according to the source dataset 116 eventhough they have been copied from the target dataset 120, where thenaming according to the source dataset 116 is performed by using asource to target extent list mapping 128 that is generated during thepoint-in-time copy operations 118.

Therefore, FIG. 1 illustrates certain embodiments in which apoint-in-time backup copy of a source dataset 116 is made to a storagecloud 106 by the storage controller 102. In prior art, the copying ofthe tracks of the target dataset 120 to the backup dataset 124 wasperformed by the host 104 by receiving from the storage controller 102the data stored in the tracks of the target dataset 120 and then copyingthe received data to the backup dataset 124. Additionally, there was noprovision for maintaining the source to target extent list mapping 128in the prior art.

FIG. 2 illustrates a block diagram 200 that shows the generation of apoint-in-time backup dataset via mapping of individual extents, inaccordance with certain embodiments.

in FIG. 2, four source dataset objects shown as extents A1, A2, A3, A4204, 206, 208, 210 of the source data set 116 are copied viapoint-in-time copy operations to four corresponding dataset objectsshown as extents B1, B2, B3, B4 212, 214, 216, 218 of the target dataset120. The dataset objects shown as extents B1, B2, B3, B4 212, 214, 216,218 of the target dataset 120 are concurrently copied to the backupdataset 124 but renamed as extents A1, A2, A3, A4 220, 222, 224, 226 byusing the source to target extent list mapping 128 which shows thecorrespondences 130 between the names of the source extents and thetarget extents.

Additionally, FIG. 2 also shows that a large extent A5 228 of the sourcedataset 116 may be copied via point-in-time copy operations to twosmaller extents B5, B6 230, 232 of the target dataset 120. The datasetobject shown as extents B5, B6 230, 232 of the target dataset 120 areconcurrently copied to the backup dataset 124 but renamed as extent A5234 by using the source to target extent list mapping 128 which showsthe correspondences 130 between the names of the source extents and thetarget extents.

Furthermore, FIG. 2 also shows that two small extents A6, A7 236, 238 ofthe source dataset 116 may be copied via point-in-time copy operationsto a large extent B7 240 of the target dataset 120. The dataset objectshown as extent B7 240 of the target dataset 120 is concurrently copiedto the backup dataset 124 but renamed as extents A6, A7 242. 244 byusing the source to target extent list mapping 128 which shows thecorrespondences 130 between the names of the source extents and thetarget extents.

As a result, the objects of the backup dataset 124 have the same namesas the objects of the source dataset 116 and do not have the names ofthe objects of the target dataset 120. As a result, the backup dataset124 may be accessed with same object names as the source dataset 116. Itmay be noted that the correspondences 130 between the names of thesource extents and the target extents may be one to one, one to many ormany to one.

FIG. 3 illustrates a block diagram 300 that shows the generation of apoint-in-time backup dataset via mapping of extent ranges, in accordancewith certain embodiments.

In FIG. 3, the data records stored in the source dataset 116 are in anextent range 100-200 (shown via reference numeral 302) and are copiedvia point-in-time copy operations into the target dataset 120 into datarecords that are in extent range 500-600 (shown via reference numeral304). However, when the target dataset 120 is concurrently copied to thebackup dataset 124, then the extent range 500-600 is indicated as beingin extent range 100-200 (shown via reference numeral 306) in the backupdataset 124, by using the source to target extent list mapping 128 thathas the mapping 330 that indicates that extent range 100-200 of thesource dataset 116 has been mapped to extent range 500-600 of the targetdataset 120. As a result, the backup dataset 124 may be accessed withsame extent ranges as the source dataset 116.

FIG. 4 illustrates a diagram 400 that shows the generation of apoint-in-time backup dataset via mapping of volumes and cylinders, inaccordance with certain embodiments.

Control starts at block 402 in which the storage controller 102 receivesa command from the host 104 to backup Volume 1, Cylinders 201-300 wheretracks of the source dataset 116 are stored. As a result of thepoint-in-time copy operations 118, the point-in-time copy data is storedon Volume 2, Cylinders 601-700 where the tracks of the target dataset120 are stored (as shown via reference numeral 404). The storagecontroller 102 is directed to copy (at block 406) Volume 2, Cylinders601-700 where the tracks of the target dataset 120 are stored, to thestorage cloud 106, but an indication is made in the storage cloud 106that the data is stored as backup dataset in volume 1, Cylinders201-300. The indication may be made by using the mapping 128 or viaother mechanisms. As a result, the backup dataset 124 may be accessedwith the same volume name and cylinder range as the source dataset 116.

FIG. 5 illustrates a first flowchart 500 that shows generation of apoint-in-time backup dataset, in accordance with certain embodiments.The operations shown in FIG. 5 may be performed by the storagecontroller 102.

Control starts at block 502 in which the storage controller 102 collectsdata of the source dataset 116 and establishes a point in time copy ofthe tracks of the source dataset 116 into the target dataset 120.Control proceeds to block 504 in which the storage controller 102 copiesthe tracks from the target dataset 120 to the storage cloud 106, withoutsending the tracks of the target dataset 120 to the host 104.

FIG. 6 illustrates a second flowchart 600 that shows generation of apoint-in-time backup dataset, in accordance with certain embodiments.The operations shown in FIG. 6 may be performed by the storagecontroller 102.

Control starts at block 602 in which the storage controller 102 buildsan extent list of the source dataset 116, and establishes (at block 604)a virtual concurrent copy session. The storage controller 102 generates(at block 606) the source to target extent list mapping 128, and buildsa request to offload target tracks to cloud storage (at block 608).

From block 608 control proceeds to block 610 in which the storagecontroller 102 sends target tracks to cloud storage 106 (instead ofsending tracks via the host 104 as in prior art).

After an interval of time, in response to termination of the virtualconcurrent copy session, resources allocated for the source to targetextent list mapping 128 are freed (at block 612) as they are no longerof any use and as a result memory is freed.

In parallel with the operations being performed in blocks 606, 608, 610(shown via reference numeral 614), control may proceed to block 616. Inblock 616, an I/O request from the host 104 is received by the storagecontroller 102. A determination is made (at block 618) as to whethertracks corresponding to the I/O request have been updated in the targetdataset 120. If so (“Yes” branch 620) control proceeds to block 622 inwhich the storage controller 102 sends the I/O request to the targetdataset extents for tracks that have been updated in the target dataset120.

If at block 618, it is determined that tracks corresponding to the I/Orequest have not been updated in the target dataset 120 (“No” branch624) then control proceeds to block 626 in which the storage controller102 redirects I/O requests to the source dataset extents for tracks thathave not been updated in the target dataset 120.

Therefore, FIG. 6 illustrates certain embodiments in which a backupdataset 124 is generated under the control of a storage controller 102via a combination of a point-in-time copy of the source dataset 116 tothe target dataset 120, and a concurrent copy from the target dataset120 to the backup dataset 126, with the process being referred to as avirtual concurrent copy under the control of the storage controller.

FIG. 7 illustrates a third flowchart 700 that shows generation of apoint-in-time backup dataset, in accordance with certain embodiments.The operations shown in FIG. 7 may be performed by the storagecontroller 102.

Control starts at block 702 in which a storage controller 102 receives acommand from a host application 110 to perform a point-in-time backup ofa source dataset 116 to a storage cloud 106. The storage controller 102generates (at block 704) a target dataset 120 via a point-in-time copyof the source dataset 116 and a mapping 128 that indicates acorrespondence between locations of the source dataset and locations ofthe target dataset.

From block 704 control proceeds to block 706 in which the storagecontroller 102 copies the target dataset 120 to the storage cloud 106 togenerate a backup dataset 124 that is the point-in-time backup of thesource dataset 116, where the backup dataset 124 is accessible viareference to the locations of the source dataset

From block 704 control may also proceed to block 708 in which thestorage controller 102 receives an I/O request from a host computationaldevice 104. From block 708, control may proceed in parallel to block710, 712.

At block 710, in response to determining that a track corresponding tothe I/O request has been updated in the target dataset 120, the storagecontroller 102 sends the I/O request to target dataset extents for thetrack, and the I/O request is satisfied by the target dataset 120.

At block 712, in response to determining that a track corresponding tothe I/O request has not been updated in the target dataset 120, thestorage controller 102 sends the I/O request to source dataset extentsfor the track, and the I/O request is satisfied by the source dataset116.

Therefore, in FIGS. 1-7, the operations for performing the point-in-timebackup of the source dataset 116 to the storage cloud 106 is offloadedto the storage controller 102 from the host computational device 104.The storage controller 102 copies the target dataset 120 to the storagecloud 106 without transmitting extents, tracks, or other storageentities of the target dataset 120 to the host computational device 104.In certain embodiments, a mapping 128 indicates a correspondence betweenthe locations of the source dataset and the locations of the targetdataset, where the mapping maps individual extents, or extent ranges, orvolumes and associated cylinder ranges. The mapping 128 is used to namethe backup dataset 124 to reflect locations of the source dataset 116,and as a result the backup dataset 124 is accessed analogously to thesource dataset 116.

Cloud Computing Environment

Cloud computing is a model for enabling convenient, on-demand networkaccess to a shared pool of configurable computing resources (e.g.,networks, servers, storage, applications, and services) that can berapidly provisioned and released with minimal management effort orservice provider interaction.

Referring now to FIG. 8, an illustrative cloud computing environment 50is depicted. As shown, cloud computing environment 50 comprises one ormore cloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 8 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 9, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 8) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 9 are intended to be illustrative only and embodiments of theinvention are not limited thereto.

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include mainframes, in oneexample IBM zSeries* systems; RISC (Reduced Instruction Set Computer)architecture based servers, in one example IBM pSeries* systems; IBMxSeries* systems; IBM BladeCenter* systems; storage devices; networksand networking components. Examples of software components includenetwork application server software, in one example IBM WebSphere*application server software; and database software, in one example IBMDB2* database software.

Virtualization layer 62 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers;virtual storage; virtual networks, including virtual private networks;virtual applications and operating systems; and virtual clients.

In one example, management layer 64 may provide the functions describedbelow. Resource provisioning provides dynamic procurement of computingresources and other resources that are utilized to perform tasks withinthe cloud computing environment. Metering and Pricing provide costtracking as resources are utilized within the cloud computingenvironment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal provides access to the cloud computing environment forconsumers and system administrators. Service level management providescloud computing resource allocation and management such that requiredservice levels are met. Service Level Agreement (SLA) planning andfulfillment provide pre-arrangement for, and procurement of, cloudcomputing resources for which a future requirement is anticipated inaccordance with an SLA.

Workloads layer 66 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation; software development and lifecycle management; virtualclassroom education delivery; data analytics processing; transactionprocessing; and point-in-time backup to storage cloud 68 as shown inFIGS. 1-8.

Additional Embodiment Details

The described operations may be implemented as a method, apparatus orcomputer program product using standard programming and/or engineeringtechniques to produce software, firmware, hardware, or any combinationthereof. Accordingly, aspects of the embodiments may take the form of anentirely hardware embodiment, an entirely software embodiment (includingfirmware, resident software, micro-code, etc.) or an embodimentcombining software and hardware aspects that may all generally bereferred to herein as a “circuit,” “module” or “system.” Furthermore,aspects of the embodiments may take the form of a computer programproduct. The computer program product may include a computer readablestorage medium (or media) having computer readable program instructionsthereon for causing a processor to carry out aspects of the presentembodiments.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present embodiments may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present embodiments.

Aspects of the present embodiments are described herein with referenceto flowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instruction.

FIG. 10 illustrates a block diagram that shows certain elements that mayhe included in the storage controller 102, the hosts 104, or othercomputational devices in accordance with certain embodiments. The system1000 may include a circuitry 1002 that may in certain embodimentsinclude at least a processor 1004. The system 1000 may also include amemory 1006 (e.g., a volatile memory device), and storage 1008. Thestorage 1008 may include a non-volatile memory device (e.g., EEPROM,ROM, PROM, flash, firmware, programmable logic, etc.), magnetic diskdrive, optical disk drive, tape drive, etc. The storage 1008 maycomprise an internal storage device, an attached storage device and/or anetwork accessible storage device. The system 1000 may include a programlogic 1010 including code 1012 that may be loaded into the memory 1006and executed by the processor 1004 or circuitry 1002. In certainembodiments, the program logic 1010 including code 1012 may be stored inthe storage 1008. In certain other embodiments, the program logic 1010may be implemented in the circuitry 1002. One or more of the componentsin the system 1000 may communicate via a bus or via other coupling orconnection 1014. Therefore, while FIG. 10 shows the program logic 1010separately from the other elements, the program logic 1010 may beimplemented in the memory 1006 and/or the circuitry 1002.

Certain embodiments may be directed to a method for deploying computinginstruction by a person or automated processing integratingcomputer-readable code into a computing system, wherein the code incombination with the computing system is enabled to perform theoperations of the described embodiments.

The terms “an embodiment”, “embodiment”, “embodiments”, “theembodiment”, “the embodiments”, “one or more embodiments”, “someembodiments”, and “one embodiment” mean “one or more (but riot all)embodiments of the present invention(s)” unless expressly specifiedotherwise.

The terms “including”, “comprising”, “having” and variations thereofmean “including but not limited to”, unless expressly specifiedotherwise.

The enumerated listing of items does not imply that any or all of theitems are mutually exclusive, unless expressly specified otherwise.

The terms “a”, “an” and “the” mean “one or more”, unless expresslyspecified otherwise.

Devices that are in communication with each other need not be incontinuous communication with each other, unless expressly specifiedotherwise. In addition, devices that are in communication with eachother may communicate directly or indirectly through one or moreintermediaries.

A description of an embodiment with several components in communicationwith each other does not imply that all such components are required. Onthe contrary a variety of optional components are described toillustrate the wide variety of possible embodiments of the presentinvention.

Further, although process steps, method steps, algorithms or the likemay be described in a sequential order, such processes, methods andalgorithms may be configured to work in alternate orders. In otherwords, any sequence or order of steps that may be described does notnecessarily indicate a requirement that the steps be performed in thatorder. The steps of processes described herein may be performed in anyorder practical. Further, some steps may he performed simultaneously.

When a single device or article is described herein, it will be readilyapparent that more than one device/article (whether or not theycooperate) may be used in place of a single device/article. Similarly,where more than one device or article is described herein (whether ornot they cooperate), it will be readily apparent that a singledevice/article may be used in place of the more than one device orarticle or a different number of devices/articles may be used instead ofthe shown number of devices or programs. The functionality and/or thefeatures of a device may be alternatively embodied by one or more otherdevices which are not explicitly described as having suchfunctionality/features. Thus, other embodiments of the present inventionneed not include the device itself.

At least certain operations that may have been illustrated in thefigures show certain events occurring in a certain order. In alternativeembodiments, certain operations may be performed in a different order,modified or removed. Moreover, steps may be added to the above describedlogic and still conform to the described embodiments. Further,operations described herein may occur sequentially or certain operationsmay be processed in parallel. Yet further, operations may be performedby a single processing unit or by distributed processing units.

The foregoing description of various embodiments of the invention hasbeen presented for the purposes of illustration and description. It isnot intended to be exhaustive or to limit the invention to the preciseform disclosed. Many modifications and variations are possible in lightof the above teaching. It is intended that the scope of the invention belimited not by this detailed description, but rather by the claimsappended hereto. The above specification, examples and data provide acomplete description of the manufacture and use of the composition ofthe invention. Since many embodiments of the invention can be madewithout departing from the spirit and scope of the invention, theinvention resides in the claims hereinafter appended.

What is claimed is:
 1. A method, comprising: receiving, by a storagecontroller, a command from a host application to perform a point-in-timebackup of a source dataset to a storage cloud; generating, by thestorage controller, a target dataset via a point-in-time copy of thesource dataset, and a mapping that indicates a correspondence betweenlocations of the source dataset and locations of the target dataset; andcopying, by the storage controller, the target dataset to the storagecloud to generate a backup dataset that is the point-in-time backup ofthe source dataset, wherein the backup dataset is accessible viareference to the locations of the source dataset.
 2. The method of claim1, wherein the host application executes in a host computational devicethat is coupled to the storage controller, wherein operations forperforming the point-in-time backup of the source dataset to the storagecloud is offloaded to the storage controller from the host computationaldevice, and wherein the storage controller copies the target dataset tothe storage cloud without transmitting extents, tracks, or other storageentities of the target dataset to the host computational device.
 3. Themethod of claim 1, wherein in the point-in-time backup of the sourcedataset to the storage cloud is performed by a virtual concurrent copysession, the method further comprising: in response to termination ofthe virtual concurrent copy session, freeing resources allocated for themapping that indicates the correspondence between locations of thesource dataset and locations of the target dataset.
 4. The method ofclaim 1, the method further comprising: receiving, by the storagecontroller, an input/output (I/O) request from a host computationaldevice; and in response to determining that a track corresponding to theI/O request has been updated in the target dataset, sending, by thestorage controller, the I/O request to target dataset extents for thetrack.
 5. The method of claim 1, the method further comprising:receiving, by the storage controller, an input/output (I/O) request froma host computational device; and in response to determining that a trackcorresponding to the I/O request has not been updated in the targetdataset, sending, by the storage controller, the I/O request to sourcedataset extents for the track.
 6. The method of claim 1, wherein themapping that indicates a correspondence between the locations of thesource dataset and the locations of the target dataset maps individualextents, or extent ranges, or volumes and associated cylinder ranges viaone to one, many to one, and one to many correspondences.
 7. A system,comprising: a memory; and a processor coupled to the memory, wherein theprocessor performs operations, the operations comprising: receiving acommand from a host application to perform a point-in-time backup of asource dataset to a storage cloud; generating a target dataset via apoint-in-time copy of the source dataset, and a mapping that indicates acorrespondence between locations of the source dataset and locations ofthe target dataset; and copying the target dataset to the storage cloudto generate a backup dataset that is the point-in-time backup of thesource dataset, wherein the backup dataset is accessible via referenceto the locations of the source dataset.
 8. The system of claim 7,wherein the host application executes in a host computational devicethat is coupled to the system, wherein operations for performing thepoint-in-time backup of the source dataset to the storage cloud isoffloaded to the system from the host computational device, and whereinthe system copies the target dataset to the storage cloud withouttransmitting extents, tracks, or other storage entities of the targetdataset to the host computational device.
 9. The system of claim 7,wherein in the point-in-time backup of the source dataset to the storagecloud is performed by a virtual concurrent copy session, the operationsfurther comprising: in response to termination of the virtual concurrentcopy session, freeing resources allocated for the mapping that indicatesthe correspondence between locations of the source dataset and locationsof the target dataset.
 10. The system of claim 7, the operations furthercomprising: receiving an input/output (I/O) request from a hostcomputational device; and in response to determining that a trackcorresponding to the I/O request has been updated in the target dataset,sending the 110 request to target dataset extents for the track.
 11. Thesystem of claim 7, the operations further comprising: receiving aninput/output (I/O) request from a host computational device; and inresponse to determining that a track corresponding to the I/O requesthas not been updated in the target dataset, sending the I/O request tosource dataset extents for the track.
 12. The system of claim 7, whereinthe mapping that indicates a correspondence between the locations of thesource dataset and the locations of the target dataset maps individualextents, or extent ranges, or volumes and associated cylinder ranges viaone to one, many to one, and one to many correspondences.
 13. A computerprogram product, the computer program product comprising a computerreadable storage medium having computer readable program code embodiedtherewith, the computer readable program code configured to performoperations, the operations comprising: receiving, by a storagecontroller, a command from a host application to perform a point-in-timebackup of a source dataset to a storage cloud; generating, by thestorage controller, a target dataset via a point-in-time copy of thesource dataset, and a mapping that indicates a correspondence betweenlocations of the source dataset and locations of the target dataset; andcopying, by the storage controller, the target dataset to the storagecloud to generate a backup dataset that is the point-in-time backup ofthe source dataset, wherein the backup dataset is accessible viareference to the locations of the source dataset.
 14. The computerprogram product of claim 13, wherein the host application executes in ahost computational device that is coupled to the storage controller,wherein operations for performing the point-in-time backup of the sourcedataset to the storage cloud is offloaded to the storage controller fromthe host computational device, and wherein the storage controller copiesthe target dataset to the storage cloud without transmitting extents,tracks, or other storage entities of the target dataset to the hostcomputational device.
 15. The computer program product of claim 13,wherein in the point-in-time backup of the source dataset to the storagecloud is performed by a virtual concurrent copy session, the operationsfurther comprising: in response to termination of the virtual concurrentcopy session, freeing resources allocated for the mapping that indicatesthe correspondence between locations of the source dataset and locationsof the target dataset.
 16. The computer program product of claim 13, theoperations further comprising: receiving, by the storage controller, aninput/output (I/O) request from a host computational device; and inresponse to determining that a track corresponding to the I/O requesthas been updated in the target dataset, sending, by the storagecontroller, the I/O request to target dataset extents for the track. 17.The computer program product of claim 13, the operations furthercomprising: receiving, by the storage controller, an input/output (I/O)request from a host computational device; and in response to determiningthat a track corresponding to the I/O request has not been updated inthe target dataset, sending, by the storage controller, the I/O requestto source dataset extents for the track.
 18. The computer programproduct of claim 13, wherein the mapping that indicates a correspondencebetween the locations of the source dataset and the locations of thetarget dataset maps individual extents, or extent ranges, or volumes andassociated cylinder ranges via one to one, many to one, and one to manycorrespondences.
 19. A cloud computing system, comprising: a storagecloud; a storage controller coupled to the storage cloud; a host coupledto the storage controller, wherein operations performed in the cloudcomputing system, comprises: receiving, by a storage controller, acommand from a host application to perform a point-in-time backup of asource dataset to a storage cloud; generating, by the storagecontroller, a target dataset via a point-in-time copy of the sourcedataset, and a mapping that indicates a correspondence between locationsof the source dataset and locations of the target dataset; and copying,by the storage controller, the target dataset to the storage cloud togenerate a backup dataset that is the point-in-time backup of the sourcedataset, wherein the backup dataset is accessible via reference to thelocations of the source dataset.
 20. The cloud computing system of claim19, wherein the host application executes in a host computational devicethat is coupled to the storage controller, wherein operations forperforming the point-in-time backup of the source dataset to the storagecloud is offloaded to the storage controller from the host computationaldevice, and wherein the storage controller copies the target dataset tothe storage cloud without transmitting extents, tracks, or other storageentities of the target dataset to the host computational device.
 21. Thecloud computing system of claim 19, wherein in the point-in-time backupof the source dataset to the storage cloud is performed by a virtualconcurrent copy session, the operations further comprising: in responseto termination of the virtual concurrent copy session, freeing resourcesallocated for the mapping that indicates the correspondence betweenlocations of the source dataset and locations of the target dataset. 22.A host computational device, comprising: a memory; and a processorcoupled to the memory, wherein the processor performs operationscomprising: transmitting a command from a host application to a storagecontroller to perform a. point-in-time backup of a source dataset to astorage cloud, wherein the storage controller generates a target datasetvia a point-in-time copy of the source dataset, and a mapping thatindicates a correspondence between locations of the source dataset andlocations of the target dataset, and copies the target dataset to thestorage cloud to generate a backup dataset that is the point-in-timebackup of the source dataset; and accessing the backup dataset viareference to the locations of the source dataset
 23. The hostcomputational device of claim 22, wherein operations for performing thepoint-in-time backup of the source dataset to the storage cloud isoffloaded to the storage controller from the host computational device,and wherein the storage controller copies the target dataset to thestorage cloud without transmitting extents, tracks, or other storageentities of the target dataset to the host computational device.
 24. Thehost computational device of claim 22, wherein the point-in-time backupof the source dataset to the storage cloud is performed by a virtualconcurrent copy session, and wherein in response to termination of thevirtual concurrent copy session, resources allocated for the mappingthat indicates the correspondence between locations of the sourcedataset and locations of the target dataset are freed.
 25. The hostcomputational device of claim 22, wherein the host application accessesthe storage cloud via the storage controller.